synth_model_evaluation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "from utils.synth_eval import eval_sim, eval_autoreg_model_real, eval_autoreg_model_synth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "hsm_dataset_dir = Path(\"data/huge_stock_market_dataset/\")\n",
    "se_dataset_dir = Path(\"data/solar_energy/\")\n",
    "fp_dataset_dir = Path(\"data/fuel_prices/\")\n",
    "ap_dataset_dir = Path(\"data/air_passengers/\")\n",
    "results_dir = Path(\"results\")\n",
    "\n",
    "dataset_names = [\"hsm\", \"se\", \"fp\", \"ap\"]\n",
    "dataset_paths = [hsm_dataset_dir, se_dataset_dir, fp_dataset_dir, ap_dataset_dir]\n",
    "\n",
    "synth_models = [\"QuantGAN\", \"TTS_GAN\", \"RealNVP\", \"FourierFlow\", \"TimeDiffusion\"]\n",
    "autoreg_models = [\"LSTM\", \"TCN\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Handling TimeDiffusion\n",
      "processing hsm dataset\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100it [00:02, 39.53it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing se dataset\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "10it [00:00, 16.92it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing fp dataset\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "8it [00:00, 71.20it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing ap dataset\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "50it [00:30,  1.66it/s]\n"
     ]
    }
   ],
   "source": [
    "for synth_model in synth_models[4:]:\n",
    "    print(f\"Handling {synth_model}\")\n",
    "    eval_sim(dataset_names, dataset_paths, synth_model, results_dir=results_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Handling LSTM\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "0it [00:00, ?it/s]Global seed set to 0\n",
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      "10it [01:36,  9.61s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Handling TCN\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "0it [00:00, ?it/s]Global seed set to 0\n",
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      "10it [00:50,  5.07s/it]\n"
     ]
    }
   ],
   "source": [
    "for autoreg_model in autoreg_models:\n",
    "    print(f\"Handling {autoreg_model}\")\n",
    "    eval_autoreg_model_real(dataset_names[1:2], dataset_paths[1:2], autoreg_model, results_dir=results_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Handling TimeDiffusion\n",
      "Handling LSTM\n"
     ]
    },
    {
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Handling TCN\n"
     ]
    },
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     ]
    }
   ],
   "source": [
    "for synth_model in synth_models[4:]:\n",
    "    print(f\"Handling {synth_model}\")\n",
    "    for autoreg_model in autoreg_models:\n",
    "        print(f\"Handling {autoreg_model}\")\n",
    "        eval_autoreg_model_synth(dataset_names, dataset_paths, synth_model, autoreg_model, results_dir=results_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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